Proceedings of the 15th International Conference on Availability, Reliability and Security最新文献_第7页

Exploring data leakage in encrypted payload using supervised machine learning 使用监督机器学习探索加密有效载荷中的数据泄漏

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3409216

Amir Khaleghi Moghaddam, A. N. Zincir-Heywood

引用次数: 0

Network covert channels detection using data mining and hierarchical organisation of frequent sets: an initial study 使用数据挖掘和频繁集分层组织的网络隐蔽信道检测:初步研究

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3409217

P. Nowakowski, Piotr Żórawski, Krzysztof Cabaj, W. Mazurczyk

{"title":"Network covert channels detection using data mining and hierarchical organisation of frequent sets: an initial study","authors":"P. Nowakowski, Piotr Żórawski, Krzysztof Cabaj, W. Mazurczyk","doi":"10.1145/3407023.3409217","DOIUrl":"https://doi.org/10.1145/3407023.3409217","url":null,"abstract":"Currently, malware developers are increasingly turning their attention towards various types of information hiding techniques to conceal their malicious actions on the compromised machine or the network. One group of such mechanisms are network covert channels (CCs) which utilize subtle modifications to the legitimate network traffic to carry secret data. Unfortunately, nowadays no general detection approach exists that is able to fight covert communication in an efficient and scalable manner. On the contrary, typically for a given information hiding technique a dedicated detection solution is devised. That is why, in this paper we investigate possibility to utilize data mining approach to detect network covert channels: both distributed and undistributed. Specifically, we propose to rely on the hierarchical organisation of frequent sets discovered by the data mining algorithm and use it together with an outlier detection-based traffic classifier. Initial performance results reveal that the proposed solution has potential but it needs to be further evaluated in more realistic scenarios.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120968701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Memory corruption attacks within Android TEEs: a case study based on OP-TEE Android tee中的内存损坏攻击:基于OP-TEE的案例研究

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3407072

Fabian Fleischer, Marcel Busch, Phillip Kuhrt

引用次数: 7

IoT dataset generation framework for evaluating anomaly detection mechanisms 用于评估异常检测机制的物联网数据集生成框架

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3407036

Andreas Meyer-Berg, Rolf Egert, Leon Böck, M. Mühlhäuser

{"title":"IoT dataset generation framework for evaluating anomaly detection mechanisms","authors":"Andreas Meyer-Berg, Rolf Egert, Leon Böck, M. Mühlhäuser","doi":"10.1145/3407023.3407036","DOIUrl":"https://doi.org/10.1145/3407023.3407036","url":null,"abstract":"Machine learning based anomaly detection mechanisms are a promising tool to detect and protect networks from previously unknown attacks. The quality of those mechanisms strongly depends on the availability of large amounts of data for their training and evaluation. However, suitable datasets are scarce, as they are rarely shared by those who possess them. This impedes progress in the development and deployment of sophisticated machine learning mechanisms. This paper aims to accelerate this thwarted development process by introducing a network simulation framework for training-data generation and evaluation of data-driven mechanisms, like anomaly detection approaches. The framework enables training, testing, and evaluating data-driven approaches in a safe and extensible environment prior to their deployment in real-world systems. We showcase the capabilities of the framework in a case study. For this, a smart home network is modeled and simulated within the framework. The generated data is used to train an anomaly detection approach, which is then used to detect various anomalies introduced by attacks on the network. This ability to train and evaluate data-driven algorithms within the framework allows users to accelerate the otherwise time-consuming cycle of deploying, modifying, and re-training in live environments, which ultimately advances the development of novel anomaly detection approaches.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122220645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

MP2ML: a mixed-protocol machine learning framework for private inference MP2ML:用于私有推理的混合协议机器学习框架

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3407045

Fabian Boemer, Rosario Cammarota, Daniel Demmler, T. Schneider, Hossein Yalame

{"title":"MP2ML: a mixed-protocol machine learning framework for private inference","authors":"Fabian Boemer, Rosario Cammarota, Daniel Demmler, T. Schneider, Hossein Yalame","doi":"10.1145/3407023.3407045","DOIUrl":"https://doi.org/10.1145/3407023.3407045","url":null,"abstract":"Privacy-preserving machine learning (PPML) has many applications, from medical image classification and anomaly detection to financial analysis. nGraph-HE enables data scientists to perform private inference of deep learning (DL) models trained using popular frameworks such as TensorFlow. nGraph-HE computes linear layers using the CKKS homomorphic encryption (HE) scheme. The non-polynomial activation functions, such as MaxPool and ReLU, are evaluated in the clear by the data owner who obtains the intermediate feature maps. This leaks the feature maps to the data owner from which it may be possible to deduce the DL model weights. As a result, such protocols may not be suitable for deployment, especially when the DL model is intellectual property. In this work, we present MP2ML, a machine learning framework which integrates nGraph-HE and the secure two-party computation framework ABY, to overcome the limitations of leaking the intermediate feature maps to the data owner. We introduce a novel scheme for the conversion between CKKS and secure multi-party computation to execute DL inference while maintaining the privacy of both the input data and model weights. MP2ML is compatible with popular DL frameworks such as TensorFlow that can infer pre-trained neural networks with native ReLU activations. We benchmark MP2ML on the CryptoNets network with ReLU activations, on which it achieves a throughput of 33.3 images/s and an accuracy of 98.6%. This throughput matches the previous state-of-the-art work, even though our protocol is more accurate and scalable.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127507107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 80

Denial of sustainability on military tactical clouds 否认军事战术云的可持续性

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3409226

J. M. Vidal, Marco Antonio Sotelo Monge

{"title":"Denial of sustainability on military tactical clouds","authors":"J. M. Vidal, Marco Antonio Sotelo Monge","doi":"10.1145/3407023.3409226","DOIUrl":"https://doi.org/10.1145/3407023.3409226","url":null,"abstract":"As the digitalization of the military conflicts increases, gaining decision superiority become the key to enhance the likelihood of success, which among others is enabled by bringing to the tactical edge emerging ICT paradigms like advanced data fusion, Artificial Intelligence, distributed computation or end-to-trust. Based on them, Tactical Clouds will allow the provisioning of C3 services for enhancing the development of the tactical pillars of modern join military operations, like Intelligence, Surveillance, Situational Awareness, or support to decision-making. But the adoption of new technological enablers bring novel and unexplored challenges that when no remediated, may jeopardize the operability of the digital tactical assets, being the cyber defence an essential cornerstone for their safeguarding. In these grounds, the main purpose of the conducted research is to review and analyze the denial of sustainability problem on tactical combat clouds; which entails a rara avis topic on the existing bibliography among other due to the novelty, secrecy and low level of technological maturity on their related digital enablers. The research presents and scoping action that developed the following secondary objectives: 1) to frame the denial of sustainability threats on the emerging Tactical Cloud paradigm; 2) to formalize the Tactical Denial of Sustainability (TDoS) concept; 3) to introduce the phasing, potential attack surfaces, terrains and impact of TDoS attacks; 4) to illustrate heterogeneous CONOPS that facilitate the understanding of TDoS; and 5) to raise and encourage the development of further research topics and actions.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134015560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

A case study on the representativeness of public DoS network traffic data for cybersecurity research 公共DoS网络流量数据在网络安全研究中的代表性研究

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3407042

Marta Catillo, A. Pecchia, M. Rak, Umberto Villano

{"title":"A case study on the representativeness of public DoS network traffic data for cybersecurity research","authors":"Marta Catillo, A. Pecchia, M. Rak, Umberto Villano","doi":"10.1145/3407023.3407042","DOIUrl":"https://doi.org/10.1145/3407023.3407042","url":null,"abstract":"The availability of ready-to-use public security datasets is fostering measurement-driven research by a wide community of academics and practitioners. Recent trends in this area put forth a substantial body of literature on anomaly and attack detection on the top of public labelled datasets. Much of this literature blindly reuses existing datasets by overlooking the cybersecurity facets of the network traffic therein, in terms of its real impact on service availability and performance of operations. This paper addresses the representativeness of network traffic data provided by public datasets for cybersecurity research. To this aim, it proposes an initial exploration of the topic by means of a case study on Denial of Service (DoS) traffic of CICIDS2017, which is a recent dataset collected in a controlled environment that gained massive attention over the past two years. DoS traffic, which is available in CICIDS2017 in the form of packet data files, is replayed against a victim server in a controlled testbed. Measurements indicate that the DoS traffic, although somewhat relevant at network-level, has limited impact at application-level (i.e., by taking into account the performance of the victim under attack). The findings provide some key insights into the limitations of the data assessed in the study, paving the way for the construction of more rigorous datasets conceived with a multilayer perspective and that reflect actual traffic conditions under normative operations and disruptive attacks.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134178564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Relaxation time in complex network 复杂网络中的松弛时间

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3409231

D. Lande, A. Snarskii, O. Dmytrenko, I. Subach

引用次数: 2

Detection and classification of slow DoS attacks targeting network servers 针对网络服务器的慢速DoS攻击检测与分类

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3409198

E. Cambiaso, M. Aiello, M. Mongelli, I. Vaccari

引用次数: 8

Stegomalware detection through structural analysis of media files 通过媒体文件的结构分析进行隐写软件检测

Proceedings of the 15th International Conference on Availability, Reliability and Security Pub Date : 2020-08-25 DOI: 10.1145/3407023.3409187

Damian Puchalski, L. Caviglione, R. Kozik, A. Marzecki, Sławomir Krawczyk, M. Choraś

{"title":"Stegomalware detection through structural analysis of media files","authors":"Damian Puchalski, L. Caviglione, R. Kozik, A. Marzecki, Sławomir Krawczyk, M. Choraś","doi":"10.1145/3407023.3409187","DOIUrl":"https://doi.org/10.1145/3407023.3409187","url":null,"abstract":"The growing diffusion of malware is causing non-negligible economic and social costs. Unfortunately, modern attacks evolve and adapt to defensive mechanisms, and many threats are designed for the optimal exploitation of the traits of the victims. Thus, phenomena such as mobile malware, fileless malware or stegomalware are becoming widespread and represent the next variations of malicious attacks that have to be faced. In particular, the massive amount of digital content shared on the Internet is increasingly more often being used by attackers for the injection of malicious code to bypass security tools or prevent detection. Therefore, in this paper we present an approach to reveal malware and other unwanted content appended to digital images. Specifically, we address the case of pictures compressed with the Graphics Interchange Format. Since such files are based on a well-defined standard, the anomalous data can be isolated by locating the end of the file. The advantage of this approach is its simplicity, allowing to have a scalable implementation for handling huge volumes of data.","PeriodicalId":121225,"journal":{"name":"Proceedings of the 15th International Conference on Availability, Reliability and Security","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128377628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8